International Journal of Business, Economics and Management

Published by: Conscientia Beam
Online ISSN: 2312-0916
Print ISSN: 2312-5772
Quick Submission    Login/Submit/Track

No. 2

Research on the Construction and Application of Chinese Enterprises Overseas Port Investment Confidence Index Based on D-S Evidence Theory

Pages: 134-153
Find References

Finding References

Research on the Construction and Application of Chinese Enterprises Overseas Port Investment Confidence Index Based on D-S Evidence Theory

Search :
Google Scholor
Search :
Microsoft Academic Search

DOI: 10.18488/journal.62.2021.82.134.153

Bingji Chen , Zilong Jia , Yang Liu

Export to    BibTeX   |   EndNote   |   RIS

Busse, M., & Groizard, J. L. (2008). Foreign direct investment, regulations and growth. World Economy, 31(7), 861–886.

Dihong, C., Huazhong,Li, & Xiangyu, Y. (2003). Method selection and empirical analysis of establishment of industry climate index. Systems Engineering, 21(4), 72-76.

Djankov, S., Porta, R. L., & Lopez-de-Silane, F. (2002). Courts: The lex mundi project (No. w8890). National Bureau of Economic Research.

Djankov., S., La, P. R., & Lopezdesilanes, F. (2002). The regulation of entry. The Quarterly Journal of Economics, 117(1), 1-37.

Dong, X. (2014). Thoughts on the greater role of Guangdong and Qiong provinces in the construction of the 21st century "Maritime Silk Road". Paper presented at the The Construction of the Maritime Silk Road and the Cooperation and Development of the Two Provinces of Qiong and Guangdong——The Third China (Hainan•Guangdong) ) Proceedings of Reform and Innovation Forum.

Jeong, H., Cho, H., & Jones, A. (2012). Business process models for integrated supply chain planning in open business environment. Journal of Service Science & Management, 5(1), 1-13.

Pullin, J. (2003). Canonical quantization of general relativity: the last 18 years in a nutshell[C]//AIP Conference Proceedings. American Institute of Physics, 668(1), 141-153.

Qian, Q., & Yifei, Z. (2012). The establishment and research of the global dry bulk shipping market prosperity index. Journal of Southwest University for Nationalities Natural Science Edition, 38(2), 299-304.

Research Group, P. (2008). Research on the prosperity index of China's hotel industry. Journal of Beijing International Studies University, 30(5), 1-6.

Tong, Z. (2015). Analysis of China's business environment and FDI inflows. Tianjin University of Finance and Economics.

Wenxin, P. (2015). Research on the impact of business environment in underdeveloped regions on investment promotion. Manager, 3, 155-156.

Xian-li, G. T. M. K., & Yu, L. I. U. (2003). Development and application research of composite index of iron and steel industry of China. China Industrial Economics, 11, 71-77.

Yuling, S. (2016). Research on the impact of BRIC countries’ business environment on foreign direct investment. Guangdong University of Technology, 2016, 1-55.

Zhiqiang, D., & Xiahai, W. (2012). System soft environment and economic development. Management World, 4, 9-20.

No any video found for this article.
Bingji Chen , Zilong Jia , Yang Liu (2021). Research on the Construction and Application of Chinese Enterprises Overseas Port Investment Confidence Index Based on D-S Evidence Theory. International Journal of Business, Economics and Management, 8(2): 134-153. DOI: 10.18488/journal.62.2021.82.134.153
After the "One Belt, One Road" strategy was proposed, China's overseas port investment has developed rapidly. In order to help Chinese port companies reduce their investment risks, this article provides help and suggestions for Chinese companies’ overseas port investments by establishing a port investment confidence index system. This article has established a port investment confidence index system, covering four aspects: economic scale, external links, internal vitality and institutional quality. Then, through DS evidence theory, using the subjective weights obtained from the questionnaire survey and the objective weights calculated from the data obtained from each database query to evaluate some countries along the “Belt and Road” route to prove the rationality and operability of the indicator system designed in this article And provide advice and assistance for Chinese companies’ overseas port investment. Based on the subjective weights obtained in this article, Chinese companies are more inclined to invest in economies with better internal economic development and a sound institutional environment. By comparing the objective weights of income, this paper finds that when companies invest in economies with a higher degree of development, they pay more attention to the impact of the business environment of the economy when they invest in economies with a higher degree of development. Low-level economies will give priority to the profitability and development prospects of ports when investing.
Contribution/ Originality
This article has established a port investment confidence index system, covering four aspects: economic scale, external links, internal vitality and institutional quality.

Explaining Electricity Tariffs in Kenya

Pages: 119-133
Find References

Finding References

Explaining Electricity Tariffs in Kenya

Search :
Google Scholor
Search :
Microsoft Academic Search

DOI: 10.18488/journal.62.2021.82.119.133

Grace Njeru , John Gathiaka , Peter Kimuyu

Export to    BibTeX   |   EndNote   |   RIS

AF-Mercados, E. (2018). Consultancy services for the sixth cost of service study in the electric power sub-sector. Report prepared for the Ministry of Energy and  the Energy Regulatory Commission, Madrid, Spain.

Al-Mahish, M. (2017). Economies of scale, technical change, and total factor productivity  growth of the Saudi electricity sector. International Journal of Energy Economics and Policy, 7(3), 86-94.Available at:

Berg, S. V., & Tschirhart, J. (1988). Natural monopoly regulation: Principles and  practice. New York, USA: Cambridge University Press.

Brown, D. J., & Heal, G. M. (1983). Marginal versus average cost pricing in the presence of a public monopoly. The American Economic Review, 73(2), 189-193.

Burns, P., & Weyman-Jones, T. G. (1996). Cost functions and cost efficiency in electricity distribution: A stochastic frontier approach. Bulletin of Economic Research, 48(1), 41-64.Available at:

Dramani, J. B., & Tewari, D. D. (2014). Institutions’ and electricity sectors’ performance in Ghana. Journal of Economics, 5(3), 259-273.Available at:

Electricity Regulatory Board. (2005). Retail electricity tariffs review policy. Nairobi, Kenya: Electricity Regulatory Board.

Farsi, M., Filippini, M., & Greene, W. (2006). Application of panel data models in benchmarking analysis of the electricity distribution sector. Annals of Public and cooperative Economics, 77(3), 271-290.Available at:

Filippini, M. (1998). Are municipal electricity distribution utilities natural monopolies? Annals of Public and Cooperative Economics, 69(2), 157-174.Available at:

Filippini, M., Hrovatin, N., & Zorič, J. (2004). Efficiency and regulation of the Slovenian electricity distribution companies. Energy Policy, 32(3), 335-344.Available at:

Filippini, M., & Wetzel, H. (2014). The impact of ownership unbundling on cost  efficiency: Empirical evidence from the New Zealand electricity distribution sector. Energy Economics, 45, 412-418.Available at:

Filippini, M., & Wild, J. (1998). The estimation of an average cost frontier to calculate benchmark tariffs for electricity distribution.Available at:

Filippini, M., & Wild, J. (1999). Yardstick regulation of electricity distribution utilities based on the estimation of an average cost function. Proceedings of the International Association for Energy Economics, Rome, Italy,22.Available at:

Filippini, M., & Wild, J. (2001). Regional differences in electricity distribution costs and their consequences for yardstick regulation of access prices. Energy Economics, 23(4), 477-488.Available at:

Filippini, M., Wild, J., & Kuenzle, M. (2002). Using stochastic frontier analysis for the  access price regulation of electricity networks. Lugano Switzerland: University of Italian Switzerland.

Godinho, C., & Eberhard, A. (2019). Learning from power sector reform: The case of Kenya. Policy Research Working Paper No. 8819. World Bank Group.

Gumus, E. (2007). The social costs of monopoly: A survey and an evaluation. Mediterranean IIBF Magazine, 7(13), 149-164.

Jamasb, T., & Pollitt, M. G. (2004). Benchmarking and regulation of electricity transmission and distribution utilities: lessons from international experience. Faculty of Economics, University of Cambridge, Cambridge United Kingdom. Available at: at

Jehle, G. A., & Reny, P. J. (2011). Advanced microeconomic theory (3rd ed.). Essex, England, United Kingdom: Pearson Education Ltd.

Joskow, P. L. (2005). Regulation of natural monopoly. Centre for energy and environmental policy research. Massachusetts institute of technology. Working Paper No. 05-008, Boston. Retrieved from: .

Kahn, A. E. (1998). The economics of regulation: Principles and institutions. Cambridge, Massachusetts, USA: The Massachusetts Institute of Technology Press.

Kenya, P., & Lighting, C. (2018). Annual report and financial statements. Financial Year Ended 30th June 2018. Kenya Power and Lighting Company limited, Nairobi, Kenya.

Kirschen, D., & Strbac, G. (2004). Fundamentals of power system economics. Chichester,West Sussex, England, United Kingdom: John Wiley and Sons Ltd.

Laffont, J. J. (1994). The new economics of regulation ten years after. Econometrica, 62(3), 507- 537.Available at:

Laffont, J. J. (2005). Regulation and development. Cambridge, United Kingdom: Cambridge University Press.

Laffont, J. J., & Tirole, J. (1986). Using cost observation to regulate firms. Journal of Political Economy, 94(3), 614-641.Available at:

Nelson, R. A., & Primeaux, W. J. (1988). The effects of competition on transmission and distribution costs in the municipal electric industry. Land Economics, 64(4), 338–346.Available at: https://doi:10.2307/3146306.

Neuberg, L. G. (1977). Two issues in the municipal ownership of electric power distribution systems. The Bell Journal of Economics, 8(1), 303-323.Available at:

Nillesen, P. H., & Pollitt, M. G. (2011). Ownership unbundling in electricity distribution: Empirical evidence from New Zealand. Review of Industrial Organization, 38(1), 61-93.Available at:

Pesaran, H. M., Shin, Y., & Smith, R. J. (2001). Bound testing approaches to the analysis of long run relationships. Journal of Applied Econometrics, 16(3), 289-326.Available at:

Posner, R. A. (1968). Natural monopoly and its regulation. Stanford Law Review, 21, 548-643.

Posner, R. A. (1974). Theories of economic regulation. The Bell Journal of Economics and Management Science, 5(2), 335-358.

Posner, R. A. (1999). Natural monopoly and its regulation. Washington DC: USA: Cato Institute.

Public Utility Research Center. (2012). Utility regulatory fundamentals: A reference handbook for  Public Utility Research Center training programs. Public Utility Research Center, Warrington College of Business Adminstration, University of Florida. Gainesville, Florida, USA.

Republic of Kenya. (2010). The constitution of Kenya. Nairobi, Kenya: Government Printer.

Republic of Kenya. (2019). The energy act, 2019. Nairobi, Kenya: Government Printer.

Shleifer, A. (1985). A theory of yardstick competition. The Rand Journal of Economics, 16(3), 319-327.Available at:

Stigler, G. J. (1971). The theory of economic regulation. The Bell Journal of Economics and Management Science, 2(1), 3-21.Available at: .

No any video found for this article.
Grace Njeru , John Gathiaka , Peter Kimuyu (2021). Explaining Electricity Tariffs in Kenya. International Journal of Business, Economics and Management, 8(2): 119-133. DOI: 10.18488/journal.62.2021.82.119.133
Kenya has been struggling with increasing electricity tariffs. Several regulatory reforms introduced in the sector have not succeeded in lowering the electricity tariffs necessitating the need to investigate the push factors of tariffs. This study explained electricity tariffs by exploring the drivers of Kenya Power and Lighting Company (KPLC) tariffs and the scale of operation of KPLC. Using cost time series data from KPLC for the period 1986 to 2016 and Autoregressive distributed lag model (ARDL) an average cost function for KPLC was estimated. The results indicated average tariffs of electricity increased with price of labour and system losses and decreased with output and system load factor. KPLC was found to be enjoying economies of scale and density. Transmission and distribution of power should therefore be retained as a natural monopoly. The Government of Kenya should continue reforming power supply to reduce the system losses and price of labour. Incentives aimed at increasing the system load factor such as special tariffs should be introduced.
Contribution/ Originality
This study contributes to the existing literature by estimating the drivers of KPLC tariffs and scale of operation. The findings will be useful in determining revenue requirements, setting efficiency targets and in future yardstick regulation for transmission and distribution utilities.

Innovation Efforts in the Face of Institutional Obstacles in Latin America

Pages: 100-118
Find References

Finding References

Innovation Efforts in the Face of Institutional Obstacles in Latin America

Search :
Google Scholor
Search :
Microsoft Academic Search

DOI: 10.18488/journal.62.2021.82.100.118

Priscila Rezende da Costa , Vitor da Silva Bittencourt , Christian Daniel Falaster , Luisa Margarida Cagica Carvalho , Angelica Pigola

Export to    BibTeX   |   EndNote   |   RIS

Acs, Z. J., Stam, E., Audretsch, D. B., & O’Connor, A. (2017). The lineages of the entrepreneurial ecosystem approach. Small Business Economics, 49(1), 1-10.Available at:

Alvedalen, J., & Boschma, R. (2017). A critical review of entrepreneurial ecosystems research: Towards a future research agenda. European Planning Studies, 25(6), 887-903.Available at:

Assink, M. (2006). Inhibitors of disruptive innovation capability: A conceptual model. European Journal of Innovation Management, 9(2), 215- 233.Available at:

Ayyagari, M., Demirguc-Kunt, A., & Maksimovic, V. (2012). Financing of firms in developing countries: Lessons from research. Washington, DC: The World Bank.

Baldwin, C., & Von Hippel, E. (2011). Modeling a paradigm shift: From producer innovation to user and open collaborative innovation. Organization Science, 22(6), 1399-1417.Available at:

Banalieva, E. R., Eddleston, K. A., Jiang, R. J., & Santoro, M. D. (2018). Institutional environment and the mixed gamble of internationalization. Paper presented at the Academy of Management Proceedings. Briarcliff Manor, NY 10510: Academy of Management.

Banco, M. (2018). Enterprise surveys. Retrieved from

Barasa, L., Knoben, J., Vermeulen, P., Kimuyu, P., & Kinyanjui, B. (2017). Institutions, resources and innovation in East Africa: A firm level approach. Research Policy, 46(1), 280-291.Available at:

Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.

Chae, H.-C., Koh, C. E., & Prybutok, V. R. (2014). Information technology capability and firm performance: Contradictory findings and their possible causes. Mis Quarterly, 38(1), 305-326.Available at:

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.

Cohen, W. M. (2012). Fifty years of empirical studies of innovative activity and performance. Handbook of the Economics of Innovation, 1(1), 129-213.

Colvin, J., Blackmore, C., Chimbuya, S., Collins, K., Dent, M., Goss, J., & Seddaiu, G. (2014). In search of systemic innovation for sustainable development: A design praxis emerging from a decade of social learning inquiry. Research Policy, 43(4), 760-771.Available at:

Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. London: Sage Publications.

Daniel, E. M., Ward, J. M., & Franken, A. (2014). A dynamic capabilities perspective of IS project portfolio management. The Journal of Strategic Information Systems, 23(2), 95-111.Available at:

Dau, L. A., & Cuervo-Cazurra, A. (2014). To formalize or not to formalize: Entrepreneurship and pro-market institutions. Journal of Business Venturing, 29(5), 668-686.Available at:

de-Oliveira, F., & Rodil-Marzábal, Ó. (2019). Structural characteristics and organizational determinants as obstacles to innovation in small developing countries. Technological Forecasting and Social Change, 140, 306-314.Available at:

Dib, L. A. (2008). The internationalization process of small and medium companies and the global Born phenomenon: Study of the software sector in Brazil. Rio de Janeiro: Federal University of Rio de Janeiro.

Doz, Y., & Kosonen, M. (2008). The dynamics of strategic agility: Nokia's rollercoaster experience. California Management Review, 50(3), 95-118.Available at:

Drasgow, F. (2004). Polychoric and polyserial correlations. Encyclopedia of statistical sciences, 9. New York: John Wiley & Sons.

Drnevich, P. L., & Kriauciunas, A. P. (2011). Clarifying the conditions and limits of the contributions of ordinary and dynamic capabilities to relative firm performance. Strategic Management Journal, 32(3), 254-279.Available at:

Etzkowitz, H. (2003). Research groups as ‘quasi-firms’: The invention of the entrepreneurial university. Research Policy, 32(1), 109-121.Available at:

Goedhuys, M., Janz, N., & Mohnen, P. (2014). Knowledge-based productivity in “low-tech” industries: Evidence from firms in developing countries. Industrial and Corporate Change, 23(1), 1-23.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2009). Multivariate analysis of data. Porto Alegre: Bookman Editora.

Hayes, A. F., & Montoya, A. K. (2017). A tutorial on testing, visualizing, and probing an interaction involving a multicategorical variable in linear regression analysis. Communication Methods and Measures, 11(1), 1-30.

Heimeriks, K., & Schreiner, M. (2002). Alliance capability, collaboration quality, and alliance performance: An integrated framework. Eindhoven, Netherlands: Eindhoven Center for Innovation Studies.

Hemais, C. A., & Hilal, A. (2002). The internationalization process of the firm according to the Nordic school. The internationalization of Brazilian companies: Studies of international management. Mauad: Rio de Janeiro.

Henderson, R. M., & Newell, R. G. (2011). Introduction and summary to" accelerating energy innovation: Insights from multiple sectors". In Accelerating Energy Innovation: Insights from Multiple Sectors. Chicago, EUA: University of Chicago Press.

Hollander, M., Wolfe, D. A., & Chicken, E. (2013). Nonparametric statistical methods. New York: John Wiley & Sons.

Hoyle, R. H., & Duvall, J. L. (2004). Determining the number of factors in exploratory and confirmatory factor analysis. In Kaplan, D. The Sage Handbook of quantitative methodology for the social sciences. Thousand Oaks, California: Sage Publications.

Hunt, S. D., Arnett, D. B., & Madhavaram, S. (2006). The explanatory foundations of relationship marketing theory. The Journal of Business and Industrial Marketing, 21(2), 72-87.

IBPAD. (2020). Brazilian institute of research and data analysis - Brazilian Institute of Research and Data Analysis - IBPAD, 15 Feb. Retrieved from: [Accessed 15 jan. 2020].

Jamrog, J., Vickers, M., & Bear, D. (2006). Building and sustaining a culture that supports innovation. Human Resource Planning, 29(3), 9-20.

Joshi, K. D., Chi, L., Datta, A., & Han, S. (2010). Changing the competitive landscape: Continuous innovation through IT-enabled knowledge capabilities. Information Systems Research, 21(3), 472-495.Available at:

Kanter, R. M. (2009). Knowledge management and organizational design. Washington, DC: Routledge.

Karimi, J., & Walter, Z. (2015). The role of dynamic capabilities in responding to digital disruption: A factor-based study of the newspaper industry. Journal of Management Information Systems, 32(1), 39-81.Available at:

Kaufmann, D., Kraay, A., & Mastruzzi, M. (2011). The worldwide governance indicators: Methodology and analytical issues. Hague Journal on the Rule of Law, 3(2), 220-246.

Khan, S. U., Shah, A., & Rizwan, M. F. (2019). Do financing constraints matter for technological and non-technological innovation? A (Re) examination of developing markets. Emerging Markets Finance and Trade, 12(1), 1-28.Available at:

Lai, J.-H., Chang, S.-C., & Chen, S.-S. (2010). Is experience valuable in international strategic alliances? Journal of International Management, 16(3), 247-261.Available at:

Lin, H., & Darnall, N. (2015). Strategic alliance formation and structural configuration. Journal of Business Ethics, 127(3), 549-564.Available at:

Machado, F. N. (2009). Internationalization strategies and their results: A case south of Rio-Grandense. Master's Dissertation. Federal University of Rio Grande do Sul, Porto Alegre, RS.  

Malerba, F., & McKelvey, M. (2018). Knowledge-intensive innovative entrepreneurship integrating Schumpeter, evolutionary economics, and innovation systems. Small Business Economics, 54(1), 503–522.Available at:

Matos, C. A., Henrique, J. L., & Rosa, F. (2007). The direct, mediating and moderating effects of the cost of change on consumer satisfaction and loyalty. Paper presented at the XXXI Meeting of the National Association of Graduate Studies and Research in Administration. Rio de Janeiro - RJ.

Montgomery, D. C., Peck, E. A., & Vining, G. G. (2012). Introduction to linear regression analysis. New York: John Wiley & Sons.

Oslo, O. M. (2005). Guidelines for collecting and interpreting data on innovation: Organization for Economic Cooperation and Development.

Oviatt, B. M., & McDougall, P. P. (1994). Toward a theory of international new ventures. Journal of International Business Studies, 25(1), 45-64.Available at:

Padilla-Pérez, R., & Gaudin, Y. (2014). Science, technology and innovation policies in small and developing economies: The case of Central America. Research Policy, 43(4), 749-759.Available at:

Pandit, D., Joshi, M. P., Sahay, A., & Gupta, R. K. (2018). Disruptive innovation and dynamic capabilities in emerging economies: Evidence from the Indian automotive sector. Technological Forecasting and Social Change, 129, 323-329.Available at:

Papazoglou, M. E., & Spanos, Y. E. (2018). Bridging distant technological domains: A longitudinal study of the determinants of breadth of innovation diffusion. Research Policy, 47(9), 1713-1728.Available at:

Pavlou, P. A., & El Sawy, O. A. (2006). From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development. Information Systems Research, 17(3), 198-227.Available at:

Prado, P. H. M., Korelo, J. C., & Da Silva, D. M. L. (2014). Analysis of mediation, moderation and conditional processes. Brazilian Marketing Magazine, 13(4), 04-24.

Rai, A., & Tang, X. (2010). Leveraging IT capabilities and competitive process capabilities for the management of interorganizational relationship portfolios. Information Systems Research, 21(3), 516-542.Available at:

Riaz, M. F., & Cantner, U. (2019). Revisiting the relationship between corruption and innovation in developing and emerging economies. Crime, Law and Social Change, 73(1), 395–416.Available at:

Schilke, O., & Goerzen, A. (2010). Alliance management capability: An investigation of the construct and its measurement. Journal of Management, 36(5), 1192-1219.Available at:

Sirmon, D. G., Hitt, M. A., & Ireland, R. D. (2007). Managing firm resources in dynamic environments to create value: Looking inside the black box. Academy of Management Review, 32(1), 273-292.Available at:

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533.

Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319-1350.Available at:

Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159-205.

Vassolo, R. S., Anand, J., & Folta, T. B. (2004). Non-additivity in portfolios of exploration activities: A real options-based analysis of equity alliances in biotechnology. Strategic Management Journal, 25(11), 1045-1061.Available at:

Vieira, V. A., & Faia, V. D. S. (2014). Double and triple moderating effects in the regression analysis. Paper presented at the XXXVIII Anpad Meeting. Rio de Janeiro - RJ.

Walsh, J. P., Lee, Y.-N., & Nagaoka, S. (2016). Openness and innovation in the US: Collaboration form, idea generation and implementation. Research Policy, 45(8), 1660-1671.Available at:

Waltrick, L. P. (2015). Evolution of Brazilian studies on born globals companies in international business scientific publications (Monograph). Florianópolis, SC: University of Southern Santa Catarina.

Wang, J. (2018). Innovation and government intervention: A comparison of Singapore and Hong Kong. Research Policy, 47(2), 399-412.Available at:

World Bank. (2018). World bank open data. World Bank Web. Retrieved from:

Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27(2), 185-203.Available at:

No any video found for this article.
Priscila Rezende da Costa , Vitor da Silva Bittencourt , Christian Daniel Falaster , Luisa Margarida Cagica Carvalho , Angelica Pigola (2021). Innovation Efforts in the Face of Institutional Obstacles in Latin America. International Journal of Business, Economics and Management, 8(2): 100-118. DOI: 10.18488/journal.62.2021.82.100.118
Among scholars, politicians and practitioners, innovation has become a priority. However, a consensus and convergence have yet to be reached in the literature regarding the factors that determine innovation efforts at the firm level regarding developing countries. Thus, the general aim was to gauge to what extent rapid internationalization and relational triggers enable a potential for innovation efforts in companies from Latin American countries faced with the perception of the gravity of institutional obstacles. In methodological terms, a database of the World Bank (Environment Surveys) was used, with 14,064 companies from 20 Latin American countries, with responses to question related to their innovation efforts. Unprecedented contributions were collected, as this was the first time that the perception of the gravity of institutional obstacles was jointly and empirically evaluated, together with evidence of rapid internationalization and the use of relational triggers, to explain innovation efforts, considering many firms from Latin American companies. This work also provides some clues about the potentializing effect of rapid internationalization in the relationship between institutional obstacles and innovation efforts. The main results allow a better understanding about inter- and intra-group analyses, demonstrating in which groups of Latin American company’s innovation efforts are more significant and distinctive, and therefore require pro-market and pro-internationalization public policies.
Contribution/ Originality
The paper's primary contribution is finding that what extent rapid internationalization and relational triggers potentialize the innovation efforts of Latin American companies regarding the perception of the gravity of institutional obstacles.

Some Non-Linear Problems in Accounting and Finance: Can we Apply Regression?

Pages: 81-99
Find References

Finding References

Some Non-Linear Problems in Accounting and Finance: Can we Apply Regression?

Search :
Google Scholor
Search :
Microsoft Academic Search

DOI: 10.18488/journal.62.2021.82.81.99

John Ogwang

Export to    BibTeX   |   EndNote   |   RIS

Almenberg, J., & Gerdes, C. (2011). Exponential growth bias and financial literacy. IZA Discussion Paper No. 5814 June 2011.

Ayenew, W. (2016). Determinants of tax revenue in Ethiopia (Johansen co-integration approach). International Journal of Business, Economics and Management, 3(6), 69-84.Available at:

Benoit, K. (2011). Linear regression models with logarithmic transformations. London: London School of Economics.

Drury, C. (2008). Management and cost accounting   (12th ed.). Hampshire, U.K  Cengage Learning.

Francis, A. (2004). Business Mathematics and statistics (6th ed.). Hampshire, U.K: Cengage Learning.

Goda, G. S., & Sojourner, A. (2012). What will my account really be worth? An experiment on exponential growth bias and retirement saving. NBER  Working Paper 17927.

Herwartz, H., & Weber, H. (2005). Exchange rate uncertainty and trade growth—a comparison of linear and non-linear (forecasting) models. Applied Stochastic Models in Business and Industry, 21(1), 1-26.

Jaisinghani, D., & Kanjilal, K. (2017). Non-linear dynamics of size, capital structure and profitability: Empirical evidence from Indian manufacturing sector. Asia Pacific Management Review, 22(3), 159-165.Available at:

Johnston, J., & DiNardo, J. (1997). Econometric methods (4th ed.). Ney York, United States: McGraw Hill.

Lapašinskaitė, R., & Boguslauskas, V. (2006). Non-linear time-cost break even research in product lifecycle. Engineering Economics, 46(1), 7-12.

Levy, M. R., & Tasoff, J. (2017). Exponential-growth bias and overconfidence. Journal of Economic Psychology, 58, 1-14.Available at:

Lucey, T. (2002). Quantitative techniques. London: Cengage Learning.

Madura, J. (2015). International Financial Management (12th ed.). Singapore: Cengage Learning, New Tech Park.

McMillan, D. G. (2012). Does non-linearity help us understand, model and forecast UK stock and bond returns: evidence from the BEYR. International Review of Applied Economics, 26(1), 125-143.Available at:

Munteanu, A., & Mehedintu, G. (2016). The importance of facility management in the life cycle costing calculation. Review of General Management, 23(1), 65-77.

Rusov, J., Misita, M., Milanovic, D. D., & Milanovic, D. L. (2017). Applying regression models to predict business results. FME Transactions, 45(1), 198-202.Available at:

Saha, S., & Yap, G. (2015). Corruption and tourism: An empirical investigation in a non-linear framework. International Journal of Tourism Research, 17(3), 272-281.Available at:

Savić, B., Milojević, I., & Petrovic, V. (2019). Cost optimization in agribusiness based on life cycle costing. Economics of Agriculture, 66(3), 823-834.Available at:

Stango, V., & Zinman, J. (2009). Exponential growth bias and household finance. The Journal of Finance, 64(6), 2807-2849.Available at:

Thanatawee, Y. (2016). The non-linear impact of share repurchases on liquidity: The case of listed companies in Thailand. Asian Journal of Business and Accounting, 9(1), 1-29.

Vatavo, S. (2016). Non-linear panel data analysis for capital Structure and its Impacts on Profitability. The Review of Finance and Banking, 8(1), 21 - 36.

Wu, D., & Li, J. (2017). Applications of nonlinear models in contribution margin and profit analysis. Journal of Business Cases and Applications, 16.

No any video found for this article.
John Ogwang (2021). Some Non-Linear Problems in Accounting and Finance: Can we Apply Regression?. International Journal of Business, Economics and Management, 8(2): 81-99. DOI: 10.18488/journal.62.2021.82.81.99
Recent studies have indicated that many decision problems in accounting and finance can be better modeled by non-linear models in practice. However, existing literatures have also shown that managers and decision makers are not very conversant with non-linear models as compared to linear models because of the simplicity of linear models. In this paper, attempts are made to transform some non-linear models in accounting and finance which conform to exponential and power functions to their equivalent linear forms. The resulting equivalent linear models are subjected to regression analysis. The paper documents interesting practical non-linear problems in accounting and finance where it is possible to apply regression, and provides technical interpretations of coefficients of resulting regression equations. Some non-linear problems which have been documented in this analysis include; depreciation of non-current assets, the learning curve model, life cycle costing, compounding, discounting and exponential growth bias. Although logarithmic transformation of non- linear functions is not a novel idea in literature of accounting and finance, there is no evidence in literature that scholars have proposed particular cases in finance and accounting where these linear transformations and their resulting regression equations would yield meaningful results that can enhance management decision making. This paper fills this gap by documenting practical non-linear problems in finance and accounting where linearization and subsequent application of regression analysis generates useful results for management decision making purposes.
Contribution/ Originality
In the literature of accounting and finance specifically; firstly, this paper originates new formulae for some non-linear problems. Secondly, it’s among very few papers which examined regression of non-linear problems. Thirdly, this is the first paper to document practical cases where regression of log transformed variables generates useful results.

Brexit Calling! Aftermath in the Pharmaceutical Industry

Pages: 70-80
Find References

Finding References

Brexit Calling! Aftermath in the Pharmaceutical Industry

Search :
Google Scholor
Search :
Microsoft Academic Search

DOI: 10.18488/journal.62.2021.82.70.80

Haritini Tsangari , Ioanna Mantara

Export to    BibTeX   |   EndNote   |   RIS

AstraZeneca. (n.d). AstraZeneca Global Site. Retrieved from: Htps:// [Accessed December 11, 2018].

AstraZeneca Plc. (2019). Fort Mill: Mergent. Retrieved from:

Bayer. (2019). Our political principles and positions. Retrieved from: [Accessed October 27, 2019].

Bayer. (n.d). Bayer company official website. Retrieved from: [Accessed December 11, 2018].

Beaudry, P., & Portier, F. (2006). Stock prices, news, and economic fluctuations. American Economic Review, 96(4), 1293-1307.Available at:

Beaulieu, M.-C., Cosset, J.-C., & Essaddam, N. (2006). Political uncertainty and stock market returns: Evidence from the 1995 Quebec referendum. Canadian Journal of Economics, 39(2), 621-642.Available at:

Benartzi, S., & Thaler, R. H. (1995). Myopic loss aversion and the equity premium puzzle. The Quarterly Journal of Economics, 110(1), 73-92.

Benartzi., S., & Thaler, R. H. (1999). Risk aversion or myopia? Choices in repeated gambles and retirement investments. Management Science, 45(3), 364-381.

Beynon, K., & Porter, A. (2000). Valuing pharmaceutical companies: A guide to the assessment and evaluation of assets, performance and prospects. Cambridge: Woodhead.

Bloom, N., Bunn, P., Chen, S., Mizen, P., Smietanka, P., Thwaites, G., & Young, G. (2019a). Brexit and uncertainty: Insights from the decision maker panel. Bank of England Working Paper No. 780.

Bloom, N., Bunn, P., Chen, S., Mizen, P., Smietanka, P., Thwaites, G., & Young, G. (2019b). The impact of brexit on UK firms: Reduced investments and decreased productivity. NBER Working Paper No. 26218.

Born, B., Müller, G., Schularick, M., & Sedlacek, P. (2017). The economic consequences of the brexit vote. Discussion Papers No.1738, Centre for Macroeconomics (CFM).

Breinlich, H., Leromain, E., Novy, D., Sampson, T., & Usman, A. (2018). The economic effects of Brexit: Evidence from the stock market. Fiscal Studies, 39(4), 581-623.

Brett, D. (2017). Why stockmarkets rise when currencies fall. March 2017. Retrieved from [Accessed December 11, 2018].

Christie, A. A. (1982). The stochastic behavior of common stock variances: Value, leverage and interest rate effects. Journal of Financial Economics, 10(4), 407-432.Available at:

CNNMoney. (n.d). Fear & greed index. Retrieved from: [Accessed December 11, 2018].

Davies, R., & Studnicka, Z. (2018). The heterogeneous impact of Brexit: Early indications from the FTSE. European Economic Review, 110, 1-17.Available at:

De Bondt, W. F., & Thaler, R. (1985). Does the stock market overreact? The Journal of Finance, 40(3), 793-805.Available at:

European Federation of Pharmaceutical Industries and Associations. (2017). EFPIA brexit briefing. Retrieved from [Accessed September 27, 2018].

European Federation of Pharmaceutical Industries and Associations. (2019). The pharmaceutical industry in figures. Retrieved from: [Accessed February 19, 2020].

European Medicines Agency. (2019). EMA now operating from Amsterdam. Retrieved from [Accessed March 12, 2020]

Fama, E. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383-417.

GlaxoSmithKline. (n.d). GSK company official site. Retrieved from: [Accessed December 11, 2018].

GlaxoSmithKline Plc. (2019). Fort mill: Mergent. business market research collection. Retrieved from:

Hashemian-Rahaghi, S., Cheng, F., & Farnaz, A. (2017). Production efficiency and financial performance in pharmaceutical industry: A case of top 24 companies. (August 4, 2017). Available at SSRN Electronic Journal or

Hens, T., & Meier, A. (2015). Behavioral finance: The psychology of investing. White Paper, Credit Suisse Group, USA. Retrieved from: [Accessed February 19, 2019].

Hoovers. (n.d). Hoover's company profiles. Retrieved from: [Accessed December 11, 2018].

Jorion, P., & Goetzmann, W. N. (1999). Global stock markets in the twentieth century. The Journal of Finance, 54(3), 953-980.Available at:

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.

Kazzazi, F., Pollard, C., Tern, P., Ayuso-Garcia, A., Gillespie, J., & Thomsen, I. (2017). Evaluating the impact of Brexit on the pharmaceutical industry. Journal of Pharmaceutical Policy and Practice, 10(1), 1-12.Available at:

Kollewe, J., & Scruton, P. (2019). What are Brexit contingency plans for pharmaceutical industry?. The Guardian. Retrieved from [Accessed February 3, 2019].

Lauerman, J., & Ring, S. (2020). U.S. Raises ante in vaccine race with $1.2 Billion for Astra, Bloomberg. Retrieved from: [Accessed June 2, 2020].

London Stock Exchange. (2020). Agreement to supply Europe with COVID-19 vaccine. Retrieved from: [Accessed June 2, 2020].

Malkiel, B. G. (1973). A random walk down wall street. New York: W. W. Norton & Co.

Markovitch, D. G., Steckel, J. H., & Yeung, B. (2005). Using capital markets as market intelligence: Evidence from the pharmaceutical industry. Management Science, 51(10), 1467-1480.

McKee, M., & Martin, J. (2016). How Brexit will affect healthcare, science and research. The Pharmaceutical Journal, 296.

Nicholls, A. (2016). SmartViews: Brexit - What’s next for pharma? Retrieved from [Accessed October 12, 2019].

Novartis, A. (2019). Fort Mill: Mergent. Retrieved from:

Novartis, A. (n.d). Novartis company official website. Retrieved from: [Accessed December 11, 2018].

NSF International. (2017). Brexit implications for the UK pharmaceutical industry. York, UK: NSF.

Papastavrou, E., Tsangari, H., Karayiannis, G., Papacostas, S., Efstathiou, G., & Sourtzi, P. (2011). Caring and coping: The dementia caregivers. Aging & Mental Health, 15(6), 702-711.Available at:

Partington, R. (2019). How has Brexit vote affected the UK economy? October verdict. The Guardian. Retrieved from [Accessed February 3, 2020].

Redl, C. (2017). The impact of uncertainty shocks in the United Kingdom. Bank of England Staff Working Paper No.695.

Rogers, L., & Satchell, S. (1991). Estimating variance from high, low and closing prices. The Annals of Applied Probability, 1(4), 504-512.Available at:

Rogers, L. C., Satchell, S. E., & Yoon, Y. (1994). Estimating the volatility of stock prices: A comparison of methods that use high and low prices. Applied Financial Economics, 4(3), 241-247.Available at:

Sattar, S., Hughes, T., & Marshall, J. (2017). The implications of Brexit on the UK Nhs and the UK pharmaceutical industry. Value in Health, 20(9), A703-A704.Available at:

Schwert, G. W. (2003). Anomalies and market efficiency. In G. Constantinides et al. (Eds.), Handbook of the Economics of Finance (1st ed., Vol. 1, pp. 939-974): Elsevier.

Shefrin, H., & Statman, M. (2000). Behavioral portfolio theory. Journal of Financial and Quantitative Analysis, 35(2), 127-151.

Shiller, R. J. (2003). From efficient markets theory to behavioral finance. Journal of Economic Perspectives, 17(1), 83-104.

Szyszka, A. (2013). Behavioral finance and capital markets: How psychology influences investors and corporations. New York: Palgrave Macmillan.

Tsangari, H. (2007). An alternative methodology for combining different forecasting models. Journal of Applied Statistics, 34(4), 403-421.Available at:

UK Parliament Publications. (2018). The impact of Brexit on the pharmaceutical sector. Retrieved from [Accessed May 17, 2019].

No any video found for this article.
Haritini Tsangari , Ioanna Mantara (2021). Brexit Calling! Aftermath in the Pharmaceutical Industry. International Journal of Business, Economics and Management, 8(2): 70-80. DOI: 10.18488/journal.62.2021.82.70.80
This paper aims to examine the impact of the Brexit referendum on the financial performance of the pharmaceutical industry in the United Kingdom. We analyze daily data for the period 1/2000-10/2019, for the two largest British pharmaceutical firms, GlaxoSmithKline and AstraZeneca, as well as two European competitors, the Swiss Novartis and the German Bayer. We perform returns and volatility analysis, financial ratio analysis and regression analysis. Our empirical results are heterogeneous among firms, pinpointing strengths and weaknesses of the pharmaceutical firms. The Brexit decision has had a significant, positive effect on the stock returns of the two British firms, a negative effect for Bayer and no effect for Novartis, while lagged returns are significant only for the European firms. At least in the short-run, both British firms have gained considerably from the depreciation of the sterling and should aim to expand their overseas network and avoid prospective trade barriers and regulatory issues.
Contribution/ Originality
This study contributes to the existing literature by examining the effect of the Brexit decision on a highly profitable sector, looking at the consequences from many different perspectives, employing various statistical techniques and focusing not only on the pharmaceutical companies in the United Kingdom, but their competitors as well.

The Euribor and EONIA Reform: Achieving Regulatory Compliance while Protecting Financial Stability

Pages: 50-69
Find References

Finding References

The Euribor and EONIA Reform: Achieving Regulatory Compliance while Protecting Financial Stability

Search :
Google Scholor
Search :
Microsoft Academic Search

DOI: 10.18488/journal.62.2021.82.50.69

Randy Priem , Ward Van Rie

Export to    BibTeX   |   EndNote   |   RIS

Abrantes-Metz, R. M., Kraten, M., Metz, A. D., & Seow, G. S. (2012). Libor manipulation? Journal of Banking & Finance, 36(1), 136-150.

Acharya, V. V., & Skeie, D. (2011). A model of liquidity hoarding and term premia in inter-bank markets. Journal of Monetary Economics, 58(5), 436-447.Available at:

Ashton, P., & Christophers, B. (2015). On arbitration, arbitrage and arbitrariness in financial markets and their governance: Unpacking LIBOR and the LIBOR scandal. Economy and Society, 44(2), 188-217.Available at:

Beirne, J. (2012). The EONIA spread before and during the crisis of 2007–2009: The role of liquidity and credit risk. Journal of International Money and Finance, 31(3), 534-551.Available at:

Bernoth, K., & Hagen, J. v. (2004). The Euribor futures market: Efficiency and the impact of ECB policy announcements. International Finance, 7(1), 1-24.Available at:

Brainbridge, S. M. (2013). Reforming Libor: Wheatley versus the alternatives. N.Y.U. Journal of Law and Business, 9(1), 789-816.

Caporale, G. M., & Gil-Alana, L. A. (2016). Persistence and cyclical dependence in the monthly euribor rate. Journal of Economics and Finance, 40(1), 157-171.Available at:

Dao, A., Godwin, A., & Ramsay, I. (2016). From enforcement to prevention: International cooperation and financial benchmark reform. Law and Financial Markets Review, 10(2), 83-101.Available at:

Duffie, D., & Stein, J. C. (2015). Reforming LIBOR and other financial market benchmarks. Journal of Economic Perspectives, 29(2), 191-212.Available at:

Eisl, A., Jankowitsch, R., & Subrahmanyam, M. G. (2017). The manipulation potential of Libor and Euribor. European Financial Management, 23(4), 604-647.

Fiszeder, P., & Pietryka, I. (2018). Monetary policy in steering the EONIA and POLONIA rates in the Eurosystem and Poland: A comparative analysis. Empirical Economics, 55(2), 445-470.Available at:

Fouquau, J., & Spieser, P. K. (2015). Statistical evidence about LIBOR manipulation: A “Sherlock Holmes” investigation. Journal of Banking & Finance, 50, 632-643.Available at:

Gandhi, P., Golez, B., Jackwerth, J. C., & Plazzi, A. (2019). Financial market misconduct and public enforcement: The case of Libor manipulation. Management Science, 65(11), 5268-5289.Available at:

Ghosh, B., Le Roux, C., & Verma, A. (2020). Investigation of the fractal footprint in selected EURIBOR panel banks. Business Perspectives, 15(1), 1-22.

Gyntelberg, J., & Wooldridge, P. D. (2008). Interbank rate fixings during the recent turmoil. BIS Quarterly Review, March, 1-14.

Hassler, U., & Nautz, D. (2008). On the persistence of the Eonia spread. Economics Letters, 101(3), 184-187.

Henrard, M. P. (2019). LIBOR fallback and quantitative finance. Risks, 7(3), 1-15.

Hou, D., & Skeie, D. (2014). Libor: Origins, economics, crisis, scandals, and reform (pp. 1-20). Federal Bank of New York Staff Report 667.

Kloster, A., & Syrstad, O. (2019). Nibor, Libor and EURIBOR – all IBORs, but different. Norges Bank Staff Memo, 2(1), 1-14.

Linzert, T., & Schmidt, S. (2011). What explains the spread between the Euro overnight rate and the ECB's policy rate? International Journal of Finance & Economics, 16(3), 275-289.Available at:

McAndrews, J., Ansani, S., & Zhenyu, W. (2008). The effect of the term auction facility of the London inter-bank offered rate (pp. 1-54). Federal Reserve Bank of New York Staff Report 335.

McConnell, P. (2013). Systemic operational risk: The LIBOR manipulation scandal. Journal of Operational Risk, 8(3), 59-99.Available at:

Michaud, F., & Upper, C. (2008). What drives interbank rates? Evidence from the Libor panel. BIS Quarterly Review, March, 1-12.

Monticini, A., & Thornton, D. L. (2013). The effect of underreporting on LIBOR rates. Journal of Macroeconomics, 37(C), 345-348.

Nautz, D., & Offermanns, C. J. (2007). The dynamic relationship between the euro overnight rate, the ECB's policy rate and the term spread. International Journal of Finance & Economics, 12(3), 287-300.

Perkins, J., & Mortby, P. (2015). Evolving financial benchmarks: The impact on legacy contracts. Journal of Securities Operations & Custody, 7(4), 296-304.

Picault, M. (2017). Pricing the ECB's forward guidance with the EONIA swap curve. International Journal of Finance & Economics, 22(2), 129-138.Available at:

Rodriguez-Lopez, A., Fernandez-Abascal, H., Maté-Garcia, J., Rodriguez-Fernandez, J., J., R.-G., & J., S.-G. (2020). Evaluating euribor manipulation: Effects on mortgage borrowers. Finance Research Letters. Forthcoming.

Schrimpf, A., & Sushko, V. (2019). Beyond LIBOR: A primer on the new benchmark rates. BIS Quarterly Review March, 1-24.

Shaw, F., Murphy, F., & O’Brien, F. G. (2016). Jumps in euribor and the effect of ECB monetary policy announcements. Environment Systems and Decisions, 36(2), 142-157.Available at:

Snider, C., & Youle, T. (2010). Does the Libor reflect banks’ borrowing costs? SSRN Working Paper, 1-25.

Taboga, M. (2014). What is a prime bank? A Euribor–OIS spread perspective. International Finance, 17(1), 51-75.Available at:

Vergote, O., & Gutiérrez, J. M. P. (2012). Interest rate expectations and uncertainty during ECB governing council days: Evidence from intraday implied densities of 3-month Euribor. Journal of Banking & Finance, 36(10), 2804-2823.

Yeoh, P. (2016). Libor benchmark: Practice, crime and reforms. Journal of Financial Crime, 23(4), 1140-1153.

No any video found for this article.
Randy Priem , Ward Van Rie (2021). The Euribor and EONIA Reform: Achieving Regulatory Compliance while Protecting Financial Stability. International Journal of Business, Economics and Management, 8(2): 50-69. DOI: 10.18488/journal.62.2021.82.50.69
Based on an extensive review of the academic and legal literature combined with a screening of news articles and policy papers, this article is the first to describe in great detail the events leading up to the EURIBOR reform and the efforts to make EURIBOR compliant with the European Benchmark Regulation. It documents the development of the hybrid EURIBOR methodology to ensure the benchmark to be anchored to transactions as much as possible thereby reducing manipulative behavior. The article further explains the actions undertaken by the administration and the EU RFR Working Group to transition from EONIA towards €STER and the reasoning behind the choice to recalibrate EONIA into €STER plus a spread. Although EURIBOR is considered BMR-compliant since 2 July 2019 and EONIA can continue to be used until 3 January 2022, this article explains why market participants should not be disincentivized to already take actions to provide for fallback rates to EURIBOR in their legal documentation, and to move away from EONIA. This study addresses various fallback methodologies.
Contribution/ Originality
This study is the first to provide a holistic overview of the reforms of the EURIBOR and the EONIA, as well as the on-going work to transition away from EONIA towards the Euro short-term rate (€STER). The study documents the efforts made by the administrator, the panel banks as well as by the FSMA to reform EURIBOR and to keep it operational, at least in the medium term. It explains the choice of the EU RFR Working Group and the administrator to recalibrate EONIA into €ster + a spread of 8.5 basis points.